The effect of mitochondrial DNA polymorphisms on cattle reproduction.

The aim of this study was to identify SNPs located in mitochondrial DNA that are associated with reproductive traits in beef cows. A total of 1999 Nelore females genotyped with the high-density Illumina BovineHD BeadChip (Illumina Inc., San Diego, CA, USA) were used to study the association of mitochondrial DNA variants with reproductive traits using a single-step procedure. In a preliminary analysis, the present results indicate a small participation of the mitogenome in the expression of reproductive traits in beef cattle. However, possible difficulties related to the biological characteristics of mitochondrial DNA and its inheritance, genotyping, and annotation of the phenotypes studied may also explain the results.

Mapping genomic regions for reproductive traits in beef cattle: Inclusion of the X chromosome.

Although the second largest chromosome of the genome, the X chromosome is usually excluded from genome-wide association studies (GWAS). Considering the presence and importance of genes on this chromosome that are involved in reproduction, the aim of this study was to evaluate the effect of its inclusion in GWAS on reproductive traits (scrotal circumference [SC], early pregnancy [P16] and age at first calving [AFC]) in a Nelore herd. Genotype data from 3,263 animals with the above-mentioned phenotypes were used. The results showed an increase in the variances explained by the autosomal markers for all traits when the X chromosome was not included. For SC, there was an increase of more than 10% for the windows on chromosomes 2 and 6. For P16, the effect was increased by almost 20% for windows on chromosome 5. The same pattern was found for AFC, with an increase of more than 10% for the most important windows. The results indicate that the noninclusion of the X chromosome can overestimate the effects of autosomes on SC, P16 and AFC not only because of the additive effect of the X chromosome itself but also because of its epistatic effect on autosomal genes.

Effect of genomic X-chromosome regions on Nelore bull fertility.

Scrotal circumference (SC) is a commonly used trait related to sexual precocity in bulls. Genome-wide association studies have uncovered a lot of genes related to this trait, however, only those present on autosomes. The inclusion of the second biggest chromosome (BTAX) can improve the knowledge of the genetic architecture of this trait. In this study, we performed a weighted, single-step, genome-wide association study using a 777 k BovineHD BeadChip (IllumHD) to analyze the association between SNPs and SC in Brazilian Nelore cattle. Phenotypes from 79,300 males and 3263 genotypes (2017 from females and 1246 from males)-(39,367 SNPs markers located at ChrX) were used. We identified eight regions on chromosome X that displayed important associations with SC. The results showed that together the genomic windows explained 28.52% of the genetic variance for the examined trait. Genes with potential functions in reproduction and fertility regulation were highlighted as candidates for sexual precocity rates in Nelore cattle (AFF2 and PJA1). Moreover, we found 10 genes that had not previously been identified as being associated with sexual precocity traits in cattle. These findings will further advance our understanding of the genetic architecture, considering mainly the presence of the chromosome X, for indicine cattle reproductive traits, being useful in the context of genomic prediction in beef cattle.

Influence of coat color on genetic parameter estimates in horses.

The aim of this study was to verify the effect of the inclusion of coat color on the genetic parameter estimation for linear measurements in Campolina horses. Two models (1 and 2) were applied. For model 1, coat color effect was not included as variable of the contemporary group formation; in model 2, it was included. Model 2 presented the best fitting with a Deviance Information Criterion (DIC) of -979,459.020 compared with -1,818,458.572 DIC from model 1. The average of heritability estimates ranged from low to high magnitude (0.15 to 0.53) for model 1 and from moderate to high magnitude for model 2 (0.21 to 0.47). The estimated values varied according to the analyses (models 1 and 2). The highest heritability was found for withers height (0.52), croup height (0.53), and back height (0.51). The genetic correlations ranged from values of moderate to high magnitude for models 1 (0.23 to 0.98) and 2 (0.29 to 0.99), respectively. The finding that genetic variance differed among models 1 and 2 may indicate that genotypes react differently to different coat colors, a fact implying the existence of interaction between these traits and the effect under study. The coat color influence might be explained as a pleiotropic effect of the genes that cause this phenotypic variation and also influence morphometric measures. The inclusion of the coat color effect better estimated the additive genetic variance of morphometric traits in horses. As a consequence, the genetic parameters were also more accurately estimated when it is included in the evaluation model.

Prediction of genomic breeding values for reproductive traits in Nellore heifers.

The objective of this study was to assess the accuracy of genomic predictions for female reproductive traits in Nellore cattle. A total of 1853 genotyped cows and 305,348 SNPs were used for genomic selection analyses. GBLUP, BAYESCπ, and IBLASSO were applied to estimate SNP effects. The pseudo-phenotypes used as dependent variables were: observed phenotype (PHEN), adjusted phenotype (CPHEN), estimated breeding value (EBV), and deregressed estimated breeding value (DEBV). Predictive abilities were assessed by the average correlation between CPHEN and genomic estimated breeding value (GEBV) and by the average correlation between DEBV and GEBV in the validation population. Regression coefficients of pseudo-phenotypes on GEBV in the validation population were indicators of prediction bias in GEBV. BAYESCπ showed higher predictive ability to estimate SNP effects and GEBV for all traits.

Genotype by environment interaction in Nelore cattle from five Brazilian states.

Records from 75,941 Nelore cattle were used to determine the importance of genotype by environment interaction (GEI) in five Brazilian states. (Co)variance components were estimated by single-trait analysis (with yearling weight, W450, considered to be the same trait in all states) and multiple-trait analysis (with the record from each state considered to be a different trait). The direct heritability estimates for yearling weight were 0.51, 0.39, 0.44, 0.37 and 0.41 in the states of Goiás, Mato Grosso, São Paulo, Mato Grosso do Sul and Minas Gerais, respectively. The across-state genetic correlation estimates between Goiás and Mato Grosso, Goiás and Minas Gerais, São Paulo and Minas Gerais, and Mato Grosso do Sul and Minas Gerais ranged from 0.67 to 0.75. These estimates indicate that GEIs are biologically important. No interactions were observed between Goiás and São Paulo, Goiás and Mato Grosso do Sul, Mato Grosso and São Paulo, Mato Grosso and Mato Grosso do Sul, Mato Grosso and Minas Gerais, or São Paulo and Mato Grosso do Sul (0.82 to 0.97). Comparison of single and multiple-trait analyses showed that selection based on the former was less efficient in the presence of GEI, with substantial losses (up to 10%) during selection.

Genotype by environment interaction in Nelore cattle from five Brazilian states

Records from 75,941 Nelore cattle were used to determine the importance of genotype by environment interaction (GEI) in five Brazilian states. (Co)variance components were estimated by single-trait analysis (with yearling weight, W450, considered to be the same trait in all states) and multiple-trait analysis (with the record from each state considered to be a different trait). The direct heritability estimates for yearling weight were 0.51, 0.39, 0.44, 0.37 and 0.41 in the states of Goiás, Mato Grosso, São Paulo, Mato Grosso do Sul and Minas Gerais, respectively. The across-state genetic correlation estimates between Goiás and Mato Grosso, Goiás and Minas Gerais, São Paulo and Minas Gerais, and Mato Grosso do Sul and Minas Gerais ranged from 0.67 to 0.75. These estimates indicate that GEIs are biologically important. No interactions were observed between Goiás and São Paulo, Goiás and Mato Grosso do Sul, Mato Grosso and São Paulo, Mato Grosso and Mato Grosso do Sul, Mato Grosso and Minas Gerais, or São Paulo and Mato Grosso do Sul (0.82 to 0.97). Comparison of single and multiple-trait analyses showed that selection based on the former was less efficient in the presence of GEI, with substantial losses (up to 10 percent) during selection.

Efeito da seleção para crescimento em diferentes idades sobre o consumo de energia em animais da raça Nelore

Foi avaliado o efeito da seleção para crescimento, usando como critério o peso em diferentes idades, ganhos de pesos e índices de seleção, sobre o consumo de energia de animais Nelore, usando um procedimento determinístico. Para o cálculo da resposta à seleção direta e correlacionada, foram estimados parâmetros genéticos por meio de modelos de regressão aleatória. O arquivo de dados, provenientes do Programa de Melhoramento Genético da Raça Nelore (PMGRN), continha registros de peso dos 120 dias até a idade adulta (seis anos de idade) dos animais. A exigência de energia foi calculada por meio de um procedimento determinístico, antes e após a seleção, utilizando os pesos e ganhos de pesos dos animais em equações modificadas do NRC. O efeito da seleção foi avaliado para todos os pesos padrões e ganhos de pesos usualmente utilizados, assim como para 10 tipos de índices de seleção (IND1 a IND10), os quais diferiram entre si pela ponderação dada nos pesos até o abate (positivos) e no peso adulto (PA) (negativos). Adicionalmente, utilizando como parâmetros os índices reprodutivos e de mortalidade para a raça Nelore e, utilizando os dados médios de peso por idade dos animais dos rebanhos estudados como base, foram criados rebanhos simulados, numericamente estáveis. Utilizando-se desses dados, foi possível comparar a quantidade de energia total exigida com o total de quilogramas de carne produzidos para três sistemas de produção: cria, recria e engorda para diferentes categorias animais, antes e após a seleção. O cálculo foi realizado para machos em sistema de produção de cria e completo; fêmeas na fase reprodutiva e para todos os animais em um sistema de cria, recria e engorda. O modelo de regressão aleatória definido como o mais adequado, foi o que considerou os efeitos genéticos aditivos diretos e maternos e...

The selection effect for growth on energy requirement of Nelore animals was evaluated using a deterministic process. The evaluation was made considering weights at different ages and also different selection indices. To calculate direct and correlated response of selection, the genetic parameters were obtained by random regression models. The complete data, from Nelore Cattle Breeding Program (NCBP) had ages from 120 days to mature weight of animals (six years old). The energy requirement was calculated by a deterministic process, before and after selection using weights and weights gains of animals in modified NRC equations. The selection effect was assessed considering all the weights and weights gains usually used in a breeding program and using ten different selection indices (IND1 to IND10) as well, which were different from each other by the sign of the weight, positive for weights until slaughtering and negative for mature weight (MW). Besides, a stable herd was calculated considering reproductive and mortality values of Nellore cattle, and also using the average weight in each age of all the animals. With this information a comparison was possible among the total energy consumption and kilos of meet produced, in three systems of production: cow-calf; growth and slaughtering considering different animals category before and after selection. The evaluation was done for males in a complete and cow-calf system of production; females in a reproduction stage and for all the animals in a complete system of production. The regression model that was considered the most appropriate, was defined as direct and maternal genetic effects, animal and maternal permanent environmental effects adjusted by an order of quadratic, quadratic, quartic and quadratic polynomials, respectively, and modeled by 5 classes of residual...

Interação genótipo ? ambiente no peso ao sobreano na raça Nelore

Com o objetivo de estudar a interação genótipo ? ambiente (IGA) no peso ao sobreano, foram utilizados 99.366 registros provenientes de diferentes rebanhos da raça Nelore de cinco estados brasileiros (São Paulo, Mato Grosso, Mato Grosso do Sul, Goiás e Minas Gerais). Os dados são provenientes de animais nascidos entre 1991 a 2006 participantes do Programa de Melhoramento Genético da Raça Nelore (PMGRN). As informações foram coletadas pelos próprios criadores, sendo posteriormente transferidas à Associação Nacional de Criadores e Pesquisadores (ANCP) e então incorporadas ao banco de dados. Neste estudo foram utilizados apenas os dados dos animais criados exclusivamente a pasto. Os componentes de (co)variância foram obtidos através de uma análise unicaracterística (onde considerou-se o peso como mesma característica em todos os estados) e multicaracterística (na qual considerou-se a expressão do peso em cada estado como uma característica distinta). As estimativas foram obtidas por meio de inferência bayesiana, e o modelo de análise incluiu os efeitos fixos de grupos de contemporâneos e, como aleatórios, os efeitos genético aditivo direto e residual. A interação genótipo - ambiente foi verificada através da correlação genética (rg). As interações foram consideradas importantes quando os valores de rg ficaram abaixo de 0,80. Posteriormente, verificou-se o efeito da interação sobre a seleção considerando uma análise uni ou multicaracterística. As estimativas de herdabilidade em Mato Grosso (0,39±0,03) e Mato Grosso do Sul (0,37±0,02) foram mais baixas que as encontradas em Goiás (0,51±0,02), São Paulo (0,44±0,02) e Minas Gerais (0,41±0,04). As correlações genéticas estimadas entre os pesos nos diferentes estados foram positivas...

The goal was to study genotype by environment interaction (GEI) for yearling weight. Records of 99,366 Nellore cattle from five Brazilian states (São Paulo, Mato Grosso, Mato Grosso do Sul, Goias and Minas Gerais) were used. Animals were born between 1991 to 2006 belonging to the Nellore Cattle Breeding Program (NCBP). Information was collected by farmers then, was transferred to the National Association of Breeders and Researchers (NABR) and incorporated into the database. This study used only data from animals raised exclusively on pasture. The (co)variance components were obtained using univariate (considering record as same trait in all states) and multiple-trait models, considering record from each state as a different trait. Estimates were obtained by Bayesian inference. The model for yearling weight included genetic fixed factor of contemporary groups and random animal genetic and residual effects. The genotype environment interaction was verified by genetic correlation (rg), where values below 0.80 indicated important interaction. Subsequently, the effect of interaction was verified on the selection considering a univariate or multiple-trait models. The direct heritability estimates of yearling weight in Mato Grosso (0.39±0.03) and Mato Grosso do Sul (0.37±0.02) were lower than Goiás (0.51±0.02), São Paulo (0.44±0.02) and Minas Gerais (0.41±0.04). The acrossstates estimates of genetic correlations were positive and moderate (0.67 to 0.75) between the states Goiás and Mato Grosso, Goias and Minas Gerais, São Paulo and Minas Gerais, and between Mato Grosso do Sul and Minas Gerais. These estimates indicates that genotype by environment interactions are biologically important. These results show that the animals selected will not be the same depending of the considered state, reducing the response...